Retailing TopicsRetailing Topics

RetailingMKTG 6211

Professor Edward Fox

Cox School of Business/SMU

Retail Site Selection

Openings

Expansions

Closings

What are the effects of proposed changes in retail sites What are the effects of proposed changes in retail sites on the revenues of new and existing stores?on the revenues of new and existing stores?

Retail Site SelectionWhyWhy Does It Matter?

Access to consumersNumberCharacteristicsGrowth

Locations of other storesCannibalization – own storesAgglomeration

CompetitionComplementarity

According to Wal-Mart’s Real Estate group, the difference According to Wal-Mart’s Real Estate group, the difference between good and bad locations exceed $25 million in between good and bad locations exceed $25 million in

gross profitgross profit

Retail Site SelectionHowHow Is It Done?

Select:

Geographic market

Site within the geographic market

If an opening or expansion, the format/size of the store to be opened

Retail Site SelectionAgglomeration

AgglomerationAgglomeration captures the countervailing effects of complementarity and competition among retailers Intra-type - Stores of the same type locating near

one anotherFacilitates consumer searchExamples: “motor miles” and “restaurant rows”

Inter-type - Stores of different types locating near one anotherFacilitates multi-purpose shopping, virtual one-stop-

shopping, and offers a wider variety of goods to choose from

Examples: shopping centers and shopping malls

Recognizes that consumers may use multiple Recognizes that consumers may use multiple stores to meet their needs - shopping strategically!!stores to meet their needs - shopping strategically!!

“Trip chaining” – Make unrelated purchases on the same trip

Price search – Search until you find an attractive price

“Cherry picking” – Visit multiple stores for their bargain prices

Retail Site SelectionAgglomeration

Retail Site SelectionWhere Do Consumers Work?

Another consideration in retail site selection is where consumers workDo shopping trips begin from home?From work?

Trip chainsTrip chains reflect the routing problem faced by shoppersConsumers minimize shopping costs by reducing

travel, subject to fulfilling diverse product/service needs Price searchPrice search

Our research incorporates price uncertainty, allowing shoppers to terminate or continue a shopping trip (unplanned)

Data limitations require that we:Consider visits only to selected store formatsAssume that shopping trips begin from the consumer’s

home

Retail AgglomerationTrip Chains

Retail Site SelectionAgglomeration

How does retail location affect multi-store shopping?

RETAIL LOCATIONRETAIL LOCATION

Relative to customersRelative to customers Relative to other storesRelative to other stores

Retail Competition

Retail Competition

Destination Effect

Destination Effect

Specifically, how are retailer revenues affected by nearby supermarkets, drug stores, mass merchandisers and supercenters, dollar stores and warehouse clubs?

Retail AgglomerationPreliminary Model - Data Description

Retailer N Spending PenetrationStore Visits

Travel Time (min)

BiLo 1790 $79 0.472 2.6 10.4Food Lion 1790 $184 0.785 7.1 4.9Harris Teeter 1790 $145 0.570 3.7 8.7Winn Dixie 1790 $56 0.478 2.4 8.8Wal-Mart Supercenter 1790 $122 0.617 4.0 21.2Wal-Mart Discount 1790 $30 0.343 1.7 16.8

Demographic N Average Std DevIncome (x $1,000) 358 55.1 30.3Family Size 358 2.65 1.15Head of Household Age 358 51.4 11.4College Education 358 0.38 0.49Working Woman 358 0.50 0.46

Retail AgglomerationPreliminary Model Results – Travel Times

Travel times have the expected negative effect for own-store; cross-store travel time parameters have smaller positive effects

We observe symmetric competition among grocery stores in terms of location

Revenues at EDLP stores—Food Lion and Wal-Mart Supercenter—are least sensitive to distances that their customers have to travel

Distance to

BiLo( -1.289 , -0.509 ) ( -0.075 , 0.405 ) ( -0.015 , 0.502 ) ( 0.009 , 0.737 ) ( -0.360 , 0.171 ) ( -0.025 , 0.521 )

Food Lion( -0.184 , 0.568 ) ( -0.613 , -0.182 ) ( 0.116 , 0.645 ) ( -0.204 , 0.484 ) ( -0.370 , 0.094 ) ( -0.074 , 0.360 )

Harris Teeter( -0.106 , 0.745 ) ( 0.099 , 0.678 ) ( -0.960 , -0.501 ) ( -0.146 , 0.751 ) ( -0.282 , 0.266 ) ( 0.076 , 0.591 )

Winn Dixie( 0.012 , 0.806 ) ( 0.019 , 0.429 ) ( -0.101 , 0.385 ) ( -1.222 , -0.607 ) ( 0.025 , 0.556 ) ( -0.618 , -0.218 )

WM Super( -0.818 , 0.143 ) ( -0.280 , 0.467 ) ( -0.584 , 0.105 ) ( -0.435 , 0.827 ) ( -0.778 , -0.139 ) ( -0.112 , 0.920 )

WM Discount( -0.416 , 0.504 ) ( -0.246 , 0.411 ) ( -0.334 , 0.410 ) ( -0.329 , 0.789 ) ( 0.604 , 1.432 ) ( -1.304 , -0.703 )

Resulting Revenues at

-0.416

0.333

0.133

0.250-0.095

-0.139

-0.008

0.291

-0.733

-0.460

1.015 -1.005

0.396-0.252

0.036

0.373

0.135

0.280

-0.934

0.200

0.216

0.246

0.377

-0.340

0.037

0.162

-0.400

0.390

0.223

0.096

0.081

-0.921

0.184

0.323

0.393

WM DiscountBiLo Food Lion Harris Teeter Winn Dixie WM Super

0.134

Retail AgglomerationPreliminary Model Results - Agglomeration

Wal-Mart Discount stores are most affected by locating near other stores

Wal-Mart Supercenters are not affected by the concentration of other stores nearby

Locating near club stores does not affect retailers in our sample

Agglom of

Club( -0.091 , 0.067 ) ( -0.045 , 0.013 ) ( -0.074 , 0.112 ) ( -0.092 , 0.078 ) ( -0.097 , 0.053 ) ( -0.190 , 0.092

Dollar( -0.407 , 0.257 ) ( -0.438 , 0.129 ) ( -0.616 , -0.182 ) ( -0.532 , 0.272 ) ( -1.246 , 0.846 ) ( 0.214 , 0.963

Drug( -1.226 , -0.008 ) ( -0.480 , 0.240 ) ( -0.159 , 0.866 ) ( -0.789 , 0.938 ) ( -0.170 , 0.675 ) ( 0.030 , 1.241

Grocery( -0.783 , 0.995 ) ( -0.281 , 0.495 ) ( -0.326 , 0.621 ) ( -0.703 , 0.804 ) ( -0.775 , 0.807 ) ( -2.210 , -0.173

Discount( -0.177 , 0.306 ) ( -0.086 , 0.241 ) ( 0.017 , 0.352 ) ( -0.139 , 0.275 ) ( -0.376 , 0.273 ) ( -0.086 , 0.185

Supercenter( -0.327 , -0.053 ) ( -0.051 , 0.193 ) ( -0.080 , 0.057 ) ( -0.277 , 0.105 ) ( -0.221 , 0.113 ) ( . , .

Resulting Revenues at

-1.191

0.619

0.588

-0.062-0.027

-0.197

0.255

0.012

0.349

-0.056

-0.053 .

0.0440.179

-0.016

-0.018

-0.139

0.056

0.038

0.053

-0.096

0.016

-0.405

0.057

-0.201

-0.019

-0.154

-0.114

0.117

0.075

0.068

-0.021

-0.070

-0.629

0.086

WM DiscountBiLo Food Lion Harris Teeter Winn Dixie WM Super

0.156

Multi-Channel Retailing

CCOME IN. OME IN. CCALL IN. ALL IN. LLOG ON.OG ON.

Multi-Channel Retailing

How “big” is the Internet -- milestones

Mid - 1996: online population of the United States was 35 million

Mid - 1998: online population became 72.6 million

April 1999: more than 83 million users online above age 16

2000 Census: 42% of US households have internet access

>50% of US households have computers

Source: Levy & Weitz and Census Bureau

Multi-Channel Retailing

How “big” is the Internet?

Country Jun-07 Jul-07 Growth (%) DifferenceAustralia 10,818,299 10,842,782 0.23 24,483Brazil 18,047,372 18,522,750 2.63 475,377Switzerland 3,673,908 3,717,766 1.19 43,858Germany 33,023,580 33,198,475 0.53 174,895Spain 13,999,820 13,484,624 -3.68 -515,196France 22,586,718 21,948,082 -2.83 -638,635Italy 17,197,972 17,071,177 -0.74 -126,796Japan 45,867,926 46,625,634 1.65 757,708U.K. 24,651,765 24,681,279 0.12 29,514U.S. 146,828,875 148,128,321 0.89 1,299,446Totals 336,696,235 338,220,889 0.45 1,524,654Source: Nielsen//NetRatings, 2007

Worldwide Active Internet Home Users, July 2007

Multi-Channel Retailing

How “big” is Internet retail?

Estimated Quarterly U.S. Retail E-commerce Sales as a Percent of Total Quarterly Retail Sales:4th Quarter 1999–2nd Quarter 2007

Percent of Total

                                                                                                                                                                                                                                                                                                                                                                               

Multi-Channel Retailing

What do shoppers buy on the Internet?Category Total Spend RankAirline Tickets $6,665,374 1Computer hardware $3,907,186 2Other $3,544,600 3Hotel Reservations $3,262,206 4Apparel $2,580,352 5Toys/Video Games $2,346,174 6Consumer Electronics $2,262,047 7Books $2,201,026 8Car Rental $1,660,432 9Food/Beverages $1,654,286 10Software $1,624,707 11Music $1,526,183 12Health and Beauty $1,334,326 13Office supplies $1,271,997 14Videos $1,085,490 15Jewelry $824,178 16Sporting Goods $807,614 17Linens/Home Decor $761,820 18Footwear $600,100 19Small appliances $596,605 20Flowers $590,454 21Tools and Hardware $509,188 22Furniture $443,254 23Appliances $283,579 24Garden Supplies $188,857 25

Source: PCDataonline Jan 00-Jan 01

                        

                         

Multi-Channel Retailing

What do shoppers buy on the Internet?

Selected Product Categories' Sales Growth, 2004 and 2005 (%)

  GrowthApparel and accessories 36Computer software (excludes PC games) 36Home and garden 32Toys and hobbies 32Jewelry and watches 27Event tickets 26Furniture 24Flowers, greetings, and gifts 23Notes:1. Sales exclude auctions and large corporate purchases.2. Sales are non-travel online consumer spending.Source: comScore, 2006